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Verify distribution uniformity/Chi-squared test: Difference between revisions

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Verify distribution uniformity/Chi-squared test (view source)

Revision as of 10:38, 13 May 2022

192 bytes removed ,  2 years ago
→‎{{header|Fortran}}: Use gsl_cdf_chisq_Q, simplify code and enhance readability
m (→‎{{header|Phix}}: syntax coloured)
(→‎{{header|Fortran}}: Use gsl_cdf_chisq_Q, simplify code and enhance readability)
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{{libheader|GNU Scientific Library}}
 
Instead of implementing the incompletechi-squared gamma functiondistribution by ourselves, we bind to GNU Scientific Library; so we need a module to interface to the function we need (<tt>gsl_sf_gamma_incgsl_cdf_chisq_Q</tt>)
 
<lang fortran>module GSLMiniBindgsl_mini_bind_m
implicit none
 
use iso_c_binding
interface
implicit none
real(c_double) function gsl_sf_gamma_inc(a, x) bind(C)
private
use iso_c_binding
 
real(c_double), value, intent(in) :: a, x
public :: p_value
end function gsl_sf_gamma_inc
 
end interface
interface
end module GSLMiniBind</lang>
function gsl_cdf_chisq_q(x, nu) bind(c, name='gsl_cdf_chisq_Q')
import
real(c_double), value :: x
real(c_double), value :: nu
real(c_double) :: gsl_cdf_chisq_q
end function gsl_cdf_chisq_q
end interface
 
contains
 
!> Get p-value from chi-square distribution
real function p_value(x, df)
real, intent(in) :: x
integer, intent(in) :: df
 
p_value = real(gsl_cdf_chisq_q(real(x, c_double), real(df, c_double)))
 
end function p_value
 
end module gsl_mini_bind_m</lang>
 
Now we're ready to complete the task.
 
<lang fortran>program ChiTestchi2test
use GSLMiniBind
use iso_c_binding
implicit none
 
use gsl_mini_bind_m, only: p_value
real, dimension(5) :: dset1 = (/ 199809., 200665., 199607., 200270., 199649. /)
implicit none
real, dimension(5) :: dset2 = (/ 522573., 244456., 139979., 71531., 21461. /)
 
real :: dset1(5) = [199809., 200665., 199607., 200270., 199649.]
real :: dist, prob
real :: dset2(5) = [522573., 244456., 139979., 71531., 21461.]
integer :: dof
 
real :: dist, prob
print *, "Dataset 1:"
integer :: dof
print *, dset1
dist = chi2UniformDistance(dset1)
dof = size(dset1) - 1
write(*, '(A,I4,A,F12.4)') 'dof: ', dof, ' distance: ', dist
prob = chi2Probability(dof, dist)
write(*, '(A,F9.6)') 'probability: ', prob
write(*, '(A,L)') 'uniform? ', chiIsUniform(dset1, 0.05)
 
write (*, '(A)', advance='no') "Dataset 1:"
! Lazy copy/past :|
write (*, '(5(F12.4,:,1x))') dset1
print *, "Dataset 2:"
print *, dset2
dist = chi2UniformDistance(dset2)
dof = size(dset2) - 1
write(*, '(A,I4,A,F12.4)') 'dof: ', dof, ' distance: ', dist
prob = chi2Probability(dof, dist)
write(*, '(A,F9.6)') 'probability: ', prob
write(*, '(A,L)') 'uniform? ', chiIsUniform(dset2, 0.05)
 
dist = chisq(dset1)
contains
dof = size(dset1) - 1
write (*, '(A,I4,A,F12.4)') 'dof: ', dof, ' chisq: ', dist
prob = p_value(dist, dof)
write (*, '(A,F12.4)') 'probability: ', prob
write (*, '(A,L)') 'uniform? ', prob > 0.05
 
! Lazy copy/past :|
function chi2Probability(dof, distance)
write (*, '(/A)', advance='no') "Dataset 2:"
real :: chi2Probability
write (*, '(5(F12.4,:,1x))') dset2
integer, intent(in) :: dof
real, intent(in) :: distance
 
dist = chisq(dset2)
! in order to make this work, we need linking with GSL library
dof = size(dset2) - 1
chi2Probability = gsl_sf_gamma_inc(real(0.5*dof, c_double), real(0.5*distance, c_double))
write (*, '(A,I4,A,F12.4)') 'dof: ', dof, ' chisq: ', dist
end function chi2Probability
prob = p_value(dist, dof)
write (*, '(A,F12.4)') 'probability: ', prob
write (*, '(A,L)') 'uniform? ', prob > 0.05
 
contains
function chiIsUniform(dset, significance)
logical :: chiIsUniform
real, dimension(:), intent(in) :: dset
real, intent(in) :: significance
 
!> Get chi-square value for a set of data `ds`
integer :: dof
real ::function distchisq(ds)
real, intent(in) :: ds(:)
 
real :: expected, summa
dof = size(dset) - 1
dist = chi2UniformDistance(dset)
chiIsUniform = chi2Probability(dof, dist) > significance
end function chiIsUniform
function chi2UniformDistance(ds)
real :: chi2UniformDistance
real, dimension(:), intent(in) :: ds
 
expected = sum(ds)/size(ds)
real :: expected, summa = 0.0
summa = sum((ds - expected)**2)
chisq = summa/expected
 
end function chisq
expected = sum(ds) / size(ds)
summa = sum( (ds - expected) ** 2 )
chi2UniformDistance = summa / expected
end function chi2UniformDistance
 
end program ChiTestchi2test</lang>
 
=={{header|Go}}==
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